BIOremediation systems exploiting SYnergieS for improved removal of Mixed pOllutants (BIOSYSMO)

利用协同效应改善混合污染物去除的生物修复系统 (BIOSYSMO)

• 批准号: 10045495
• 金额: $ 52.91万
• 依托单位: IMPERIAL COLLEGE LONDON
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10045495
• 关键词: BIOremediation; systems; exploiting; SYnergieS; improved

BIOSYSMO is a 48-month action that will develop a computationally-assisted framework for designing and optimizing synergistic biosystems combining the required pathways and traits to achieve the most efficient degradation and sequestration of pollutant mixtures. These biosystems will comprise combinations of bacteria, fungi and plants containing the natural or engineered pathways required for pollutants degradation and identified based on a computationally-assisted analysis. BIOSYSMO will take advantage of the high natural microbial diversity by screening samples from polluted sites and locations affected by diffuse pollution to identify natural microorganisms already present and able to metabolize the target pollutants. The search will be expanded to microorganisms previously identified and characterized by applying data mining tools to genomic and metagenomic data available in public repositories. The construction and optimization of synergistic biosystems will combine approaches based on 1) enhancing plant-microbe (bacteria, fungi) interactions to achieving combinations with improved pollutant uptake and/or degradation; 2) engineering bacteria, for improved degradation and bioaugmentation, and plants (poplar tree), for improved microbial colonization and pollutant uptake; 3) constructing artificial micro-structured consortia into aggregates and biofilms, containing all the required pathways for pollutant removal; and 4) applying bioelectrochemicalsystems(BES) asstand-alone or in hybrid systems. The different key players will be identified and combined to formulate innovative biosystems with the assistance of genome-scale metabolic (GEM) models for elucidating and simulating the key metabolic pathways. The constructed biosystems will be applied in conventional (phytoremediation, biopile, bioaugmentation) and innovative (BES, hybrid BES-phytoremediation) bioremediation approaches optimized for the treatment of mixtures of pollutants in soil, sediments and water.

BIOSYSMO是一项为期48个月的行动，将开发一个计算辅助框架，用于设计和优化协同生物系统，结合所需的途径和特征，以实现最有效的污染物混合物降解和隔离。这些生物系统将包括细菌、真菌和植物的组合，这些植物含有降解污染物所需的自然或工程途径，并根据计算辅助分析进行识别。BIOSYSMO将利用自然微生物的高度多样性，从污染地点和受弥漫污染影响的地点筛选样本，以确定已经存在并能够代谢目标污染物的自然微生物。通过将数据挖掘工具应用于公共储存库中可获得的基因组和元基因组数据，搜索将扩大到以前确定和表征的微生物。协同生物系统的构建和优化将结合以下方法：1)加强植物-微生物(细菌、真菌)的相互作用，以实现与改善污染物吸收和/或降解的结合；2)工程细菌，以改善降解和生物增强，以及植物(杨树)，以改善微生物定居和污染物吸收；3)构建人工微结构联合体，包括污染物去除所需的所有途径；以及4)单独或在杂交系统中应用生物电化学系统(BES)。不同的关键参与者将被确定并结合起来，在基因组规模代谢(GEM)模型的帮助下制定创新的生物系统，以阐明和模拟关键的代谢途径。构建的生物系统将应用于传统(植物修复、生物修复、生物强化)和创新(BES，混合BES-植物修复)生物修复方法，优化处理土壤、沉积物和水中的污染物混合物。